Responsible AI Toolkit and content moderation

Responsible AI toolkit

Nova Forge provides a Responsible AI Toolkit that includes training and evaluation data to align models to Amazon Nova's responsible AI guidelines during the training process, and runtime controls to moderate model responses during inference.

Training data – Cases and scenarios emphasizing responsible AI principles, safety considerations, and responsible technology deployment are available for data mixing to align models responsibly during continued pre-training.

Evaluations – Evaluations testing the model's ability to detect and reject inappropriate, harmful, or incorrect content are available as a benchmark task to determine the delta between base model performance and custom model performance.

Runtime controls – By default, Amazon Nova's runtime controls moderate model responses during inference. To modify these runtime controls, request Amazon Nova's Customizable Content Moderation Settings by contacting an AWS account manager.

Safety is a shared responsibility between AWS and its users. Changing the base model or using continued pre-training to improve performance on a specific use case can impact safety, fairness, and other properties of the new model. A robust adaptation method minimizes changes to the safety, fairness, and other protections built into base models while minimizing impact on model performance for tasks the model was not customized for. End-to-end testing of applications on datasets representative of use cases is required to determine if test results meet specific expectations of safety, fairness, and other properties, as well as overall effectiveness. For more information, see Amazon Web Services Responsible Use of AI Guide, Amazon Web Services Responsible AI Policy, Amazon Web Services Acceptable Use Policy, and Amazon Web Services Service Terms.